For a square matrix A=[aij] of order n, the cofactor of aij is the signed minor Aij=(−1)i+jMij (the minor Mij is the determinant left after deleting row i and column j). Replace every entry of A by its cofactor to get the cofactor matrix; its transpose is the adjoint, adjA.
Theorem (the central identity). For every square matrix A of order n,
A(adjA)=(adjA)A=∣A∣In.
This follows from Laplace expansion: a row's entries dotted with their own cofactors reproduce ∣A∣, while a row's entries dotted with a different row's cofactors always give 0 -- so the product matrix is ∣A∣ on the diagonal and 0 off it.
Definition of the inverse. A square matrix B with AB=BA=In is called the inverse of A, written A−1. The inverse, when it exists, is unique. A−1 exists if and only if A is non-singular (∣A∣=0): dividing the central identity by ∣A∣ (possible exactly when ∣A∣=0) gives the working formula
A−1=∣A∣1adjA.
A singular matrix (∣A∣=0) has no inverse.
Worked illustration (order 2). For A=(acbd), the cofactors are A11=d, A12=−c, A21=−b, A22=a, so adjA=(d−c−ba) (swap the diagonal entries, negate the off-diagonal ones) and A−1=ad−bc1(d−c−ba) whenever ad−bc=0.
Standing laws of inverses (for non-singular A,B of the same order, λ=0 a scalar):
- ∣A−1∣=∣A∣1.
- (AT)−1=(A−1)T.
- (λA)−1=λ1A−1.
- Left/right cancellation: AB=AC⇒B=C; BA=CA⇒B=C (pre/post-multiply by A−1) -- this fails when A is singular.
- Reversal law: (AB)−1=B−1A−1 (note the order flips, exactly as for transposes).
- Double inverse: (A−1)−1=A.
Six adjoint identities (non-singular A, order n): (i) adj(A−1)=(adjA)−1=∣A∣A; (ii) ∣adjA∣=∣A∣n−1; (iii) adj(adjA)=∣A∣n−2A; (iv) adj(λA)=λn−1adjA; (v) ∣adj(adjA)∣=∣A∣(n−1)2; (vi) (adjA)T=adj(AT); and for two non-singular matrices of the same order, adj(AB)=(adjB)(adjA) (order reverses, exactly like the inverse and the transpose). …